code: def test__clf_with_no_proba_pass():
      X, y = iris_data()
      clf = OneRClassifier()
      clf.fit(X, y)
  
      x_ref = X[15]
  
      res = create_counterfactual(
          x_reference=x_ref,
          y_desired=2,
          model=clf,
          X_dataset=X,
          y_desired_proba=None,
          lammbda=100,
          random_seed=123,
      )
  
      assert clf.predict(x_ref.reshape(1, -1)) == 0
      assert clf.predict(res.reshape(1, -1)) == 2
  
file_path: mlxtend/mlxtend/evaluate/tests/test_counterfactual.py
imports: import numpy
  from sklearn.linear_model import LogisticRegression
  from mlxtend.classifier import OneRClassifier
  from mlxtend.data import iris_data
  from mlxtend.evaluate import create_counterfactual
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 5 for calling a global function with example usage: test__clf_with_no_proba_pass() without return types